Paper Abstract and Keywords |
Presentation |
2019-11-05 10:00
A study of machine learning algorithm for wearable biosignal sensor Daisuke Watanabe, Yuji Yano, Shintaro Izumi, Hiroshi Kawaguchi, Masahiko Yosimoto (Kobe Univ.) MICT2019-25 MI2019-52 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The algorithm was evaluated assuming that edge inference was performed on the data obtained from the wearable biological information sensor. For three applications for wearable healthcare, we evaluated the algorithm from the viewpoint of inference accuracy and energy efficiency by implementing a random forest (RF) and convolutional neural network (CNN) with FPGA. As a result, RF increases energy efficiency by one to three orders of magnitude, making it suitable for low power applications. On the other hand, inferior accuracy, CNN is 3% to 10% high, so it is suitable for applications that require high accuracy. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
IoT / wearable healthcare / machine learning / low power inference / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 263, MICT2019-25, pp. 7-8, Nov. 2019. |
Paper # |
MICT2019-25 |
Date of Issue |
2019-10-29 (MICT, MI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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MICT2019-25 MI2019-52 |
Conference Information |
Committee |
MI MICT |
Conference Date |
2019-11-05 - 2019-11-05 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Univ. of Tsukuba |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Medical imaging technology, healthcare and medical information communication technology |
Paper Information |
Registration To |
MICT |
Conference Code |
2019-11-MI-MICT |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A study of machine learning algorithm for wearable biosignal sensor |
Sub Title (in English) |
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Keyword(1) |
IoT |
Keyword(2) |
wearable healthcare |
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machine learning |
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low power inference |
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1st Author's Name |
Daisuke Watanabe |
1st Author's Affiliation |
Kobe University (Kobe Univ.) |
2nd Author's Name |
Yuji Yano |
2nd Author's Affiliation |
Kobe University (Kobe Univ.) |
3rd Author's Name |
Shintaro Izumi |
3rd Author's Affiliation |
Kobe University (Kobe Univ.) |
4th Author's Name |
Hiroshi Kawaguchi |
4th Author's Affiliation |
Kobe University (Kobe Univ.) |
5th Author's Name |
Masahiko Yosimoto |
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Kobe University (Kobe Univ.) |
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Speaker |
Author-1 |
Date Time |
2019-11-05 10:00:00 |
Presentation Time |
20 minutes |
Registration for |
MICT |
Paper # |
MICT2019-25, MI2019-52 |
Volume (vol) |
vol.119 |
Number (no) |
no.263(MICT), no.264(MI) |
Page |
pp.7-8 |
#Pages |
2 |
Date of Issue |
2019-10-29 (MICT, MI) |
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